Understanding the impact of trades and injuries in the NHL

How important is one player to an NHL team?

The impact of deadline trades and injuries

Should bettors be concerned with trades and injuries?

Hockey stats and insights

Whether you’re betting on outrights before the season or week-to-week, an injury to a key player in the NHL often jumps out as something that could decide your bet one way or the other. NHL teams may miss players when they are injured or traded, but what impact does the absence of one player have? Read on to find out.

How important is one player to an NHL team?

Usually an individual player's impact on a team's performance is easy to exaggerate, especially in highly competitive leagues such as the NHL. While the narrative of star players that “carry” a team is easy to buy into, it is easy to forget that the differences in actual proficiency between the players are rather small, especially in the short term.

In a best-of-seven series marginal gains in probability of winning are very important.

When individuals cannot compete in a game, they are more often than not replaced by a substitute that is capable of filling the void they have left. While the player that isn’t participating may be more elite in terms of their level of performance, it is difficult to quantify this when dealing with a small sample of data.

It goes without saying that replacing the best player in the league with the worst would be a downgrade to any team, but there are several ways to compensate the missing performance by other means, such as evening out playing time or adjusting tactics.

While equally difficult to measure, it is also worth taking into consideration the motivational aspects that arise in this situation, such as handing out an opportunity for an unrated prospect which might turn out to have larger positive impact than expected.

As mentioned above, many of these motivational impacts are hard, if not impossible, to measure and predict. However, analysing the numbers from Accuscore's simulation engine does give us some useful insight into the impact one player can have on a team. Let’s have a look at an individual player’s impact on regular season results.

An easy example can be made from the case of Edmonton Oilers. Let's assume that arguably the best player in the league Connor McDavid would be out from the beginning of the season until its end and Edmonton decides not to replace their talisman forward with any acquisitions. This means that each player in that roster would simply move up a step. Here's what Accuscore's simulations determine would happen to Edmonton Oilers:

With Connor McDavid: 7th in the West, 86 points and 39 wins

Without Connor McDavid: 9th in the West, 80 points and 35 wins

This goes to show that even the best player is not necessarily the key to success, even if in this case the difference is making the playoffs or not. In Accuscore’s game simulations, individual player impact is around 3-4% at its maximum.

However, any analysis on individual players is also dependent on various factors, such as the team’s overall quality and roster depth, as well as the opponent’s respective quality. It’s also important to note that in the playoffs, the margin between victory and defeat are are very small, and teams will often benefit from even the smallest advantage or be hindered by the smallest disadvantage.

The difference between 48% probability and 51% probability for a team’s chance of winning might seem small, but when viewed in the context of a best-of-seven series it suddenly becomes very important.

The impact of the trades at the deadline

The trade deadline in the NHL was in February this year, when teams had played an average of 62 games, or approximately 75% of the 82-game regular season. This means there are 20 games for a trade to have an impact. If we consider how little one individual can impact a team over the course of the season, it’s obviously going to be a lot less when there is only 25% of the games left to play.

In Accuscore simulations, the impact of deadline trades is minimal on the regular season.

While there is a chance for a player to have a major impact in some unique cases, it is much more likely that the strength of schedule – which is a whole another topic for another article – plays a bigger part in how the trade deadline deals are seen in hindsight.

Of course the trades almost always have long standing impact regarding the future of the teams, but we’ll let those to be assessed by the team managers and other pundits. In Accuscore simulations, the impact of the deadline trades is minimal on the regular season.

For example, the Pittsburgh Penguins, who first added Jason Zucker and then Patrick Marleau, Conor Sheary and fringe player Evan Rodrigues, gained one win with those moves. The New York Islanders did the same by acquiring Jean-Gabriel Pageau and Andy Greene, although their probability to reach the playoffs also rose from 85% to 89.5%.

The Florida Panthers lost one win by letting go of Vincent Trochek and replacing him with Erik Haula and Lucas Wallmark. According to simulations, Panthers were not going to make it to the playoffs either way, but their percentage chance of achieving this took a bigger hit by falling from 41.15% to 29.66% after the deadline.

In the Western Conference, the trade deadline deals had virtually no impact according to Accuscore’s simulations.

The impact of injuries

As we have now established that individual players have a low impact on team success, let’s have a look at injuries. It is once again easy to overreact to any absence of a key player, when in reality the impact in one game is usually tiny or could even turn positive.

Although it seems obvious to mention, bettors should always remember the impact of long term injuries is somewhat different to that of trades. In trades, especially at the deadline, it is usual that another team gets considerably weaker, while the other gets stronger. When the player is injured, a team only gets weaker. In general, the team with the injured player is therefore weaker against any other team.

Let’s have a look at some recent injuries and their impacts according to Accuscore simulations:

Colorado played five games without Rantanen featuring and won all of them. The Penguins played 24 games after Guentzel got injured and they have a record of 14 win and ten losses since then. During that period, the penguins signed Jason Zucker – in the 12 games he has been on the roster, they have won four and lost eight. Jake Muzzin’s injury is an obvious blow to Toronto, but within the range of the regular season, not that crucial after all as they are on a 2-3 run without him in the team.

Using the above examples, the impact of these players can have on a single game is around 4% at maximum. If we assume Jake Guentzel miraculously recovered and was able to play in Penguins match against Anaheim after his injury, the probability of a Penguins win would be 68%, whereas without Guentzel it was 65.8%.

Should bettors be concerned with trades and injuries?

While a team you are looking to bet (or have already bet on) losing one of their start players to an injury or trade will have some degree of impact on the expected value of your bet, the extent of this is often blown out of proportion. The impacts of trades and injuries in Accuscore simulations vary depending on multiple factors, but are in general quite marginal.

Professional teams also account for this. Especially where a trade is concerned, a lot of time will be spent doing research and analysing how detrimental playing without a certain player could end up being. They have various ways to tackle the absence of an individual and in a competitive, highly professional league such as NHL, the difference in quality of the players is relatively small.

It is easy to overreact to a roster change, while the real impact as we’ve witnessed is either minimal or non-existent. The even playing field and the competitive level causes the teams to look for any small advantage available, such as that single percentage boost from a trade or other acquisitions.

Tomi studied sports sciences and business before joining Accuscore as an analyst, where he specialises in turning data into betting predictions. Tomi has close to 20 years of betting experience focusing on ice hockey, but has also spent time researching and betting on many other sports. The majority of Tomi's contributions will be based on Accuscore's predictive model.

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